Instruction stringlengths 45 106 | input_code stringlengths 1 13.7k | output_code stringlengths 1 13.7k |
|---|---|---|
Port the following code from Factor to VB with equivalent syntax and logic. | USING: accessors io kernel math math.functions math.parser
sequences ;
IN: standard-deviator
TUPLE: standard-deviator sum sum^2 n ;
: <standard-deviator> ( -- standard-deviator )
0.0 0.0 0 standard-deviator boa ;
: current-std ( standard-deviator -- std )
[ [ sum^2>> ] [ n>> ] bi / ]
[ [ sum>> ] [ n>> ] ... | data = Array(2,4,4,4,5,5,7,9)
For i = 0 To UBound(data)
WScript.StdOut.Write "value = " & data(i) &_
" running sd = " & sd(data,i)
WScript.StdOut.WriteLine
Next
Function sd(arr,n)
mean = 0
variance = 0
For j = 0 To n
mean = mean + arr(j)
Next
mean = mean/(n+1)
For k = 0 To n
variance = variance + ((arr(... |
Transform the following Factor implementation into Go, maintaining the same output and logic. | USING: accessors io kernel math math.functions math.parser
sequences ;
IN: standard-deviator
TUPLE: standard-deviator sum sum^2 n ;
: <standard-deviator> ( -- standard-deviator )
0.0 0.0 0 standard-deviator boa ;
: current-std ( standard-deviator -- std )
[ [ sum^2>> ] [ n>> ] bi / ]
[ [ sum>> ] [ n>> ] ... | package main
import (
"fmt"
"math"
)
func newRsdv() func(float64) float64 {
var n, a, q float64
return func(x float64) float64 {
n++
a1 := a+(x-a)/n
q, a = q+(x-a)*(x-a1), a1
return math.Sqrt(q/n)
}
}
func main() {
r := newRsdv()
for _, x := range []float6... |
Convert this Forth block to C, preserving its control flow and logic. | : f+! dup f@ f+ f! ;
: st-count f@ ;
: st-sum float+ f@ ;
: st-sumsq 2 floats + f@ ;
: st-mean
dup st-sum st-count f/ ;
: st-variance
dup st-sumsq
dup st-mean fdup f* dup st-count f* f-
st-count f/ ;
: st-stddev
st-variance fsqrt ;
: st-add
dup
1e dup f+! float+... | #include <stdio.h>
#include <stdlib.h>
#include <math.h>
typedef enum Action { STDDEV, MEAN, VAR, COUNT } Action;
typedef struct stat_obj_struct {
double sum, sum2;
size_t num;
Action action;
} sStatObject, *StatObject;
StatObject NewStatObject( Action action )
{
StatObject so;
so = malloc(sizeof(sSta... |
Port the following code from Forth to C# with equivalent syntax and logic. | : f+! dup f@ f+ f! ;
: st-count f@ ;
: st-sum float+ f@ ;
: st-sumsq 2 floats + f@ ;
: st-mean
dup st-sum st-count f/ ;
: st-variance
dup st-sumsq
dup st-mean fdup f* dup st-count f* f-
st-count f/ ;
: st-stddev
st-variance fsqrt ;
: st-add
dup
1e dup f+! float+... | using System;
using System.Collections.Generic;
using System.Linq;
namespace standardDeviation
{
class Program
{
static void Main(string[] args)
{
List<double> nums = new List<double> { 2, 4, 4, 4, 5, 5, 7, 9 };
for (int i = 1; i <= nums.Count; i++)
... |
Produce a functionally identical C++ code for the snippet given in Forth. | : f+! dup f@ f+ f! ;
: st-count f@ ;
: st-sum float+ f@ ;
: st-sumsq 2 floats + f@ ;
: st-mean
dup st-sum st-count f/ ;
: st-variance
dup st-sumsq
dup st-mean fdup f* dup st-count f* f-
st-count f/ ;
: st-stddev
st-variance fsqrt ;
: st-add
dup
1e dup f+! float+... | #include <assert.h>
#include <cmath>
#include <vector>
#include <iostream>
template<int N> struct MomentsAccumulator_
{
std::vector<double> m_;
MomentsAccumulator_() : m_(N + 1, 0.0) {}
void operator()(double v)
{
double inc = 1.0;
for (auto& mi : m_)
{
mi += inc;
inc *= v;
}
}
};
double Stdev(cons... |
Write a version of this Forth function in Java with identical behavior. | : f+! dup f@ f+ f! ;
: st-count f@ ;
: st-sum float+ f@ ;
: st-sumsq 2 floats + f@ ;
: st-mean
dup st-sum st-count f/ ;
: st-variance
dup st-sumsq
dup st-mean fdup f* dup st-count f* f-
st-count f/ ;
: st-stddev
st-variance fsqrt ;
: st-add
dup
1e dup f+! float+... | public class StdDev {
int n = 0;
double sum = 0;
double sum2 = 0;
public double sd(double x) {
n++;
sum += x;
sum2 += x*x;
return Math.sqrt(sum2/n - sum*sum/n/n);
}
public static void main(String[] args) {
double[] testData = {2,4,4,4,5,5,7,9};
StdDev sd = new StdDev();
... |
Produce a language-to-language conversion: from Forth to Python, same semantics. | : f+! dup f@ f+ f! ;
: st-count f@ ;
: st-sum float+ f@ ;
: st-sumsq 2 floats + f@ ;
: st-mean
dup st-sum st-count f/ ;
: st-variance
dup st-sumsq
dup st-mean fdup f* dup st-count f* f-
st-count f/ ;
: st-stddev
st-variance fsqrt ;
: st-add
dup
1e dup f+! float+... | >>> from math import sqrt
>>> def sd(x):
sd.sum += x
sd.sum2 += x*x
sd.n += 1.0
sum, sum2, n = sd.sum, sd.sum2, sd.n
return sqrt(sum2/n - sum*sum/n/n)
>>> sd.sum = sd.sum2 = sd.n = 0
>>> for value in (2,4,4,4,5,5,7,9):
print (value, sd(value))
(2, 0.0)
(4, 1.0)
(4, 0.94280904158206258... |
Write the same algorithm in VB as shown in this Forth implementation. | : f+! dup f@ f+ f! ;
: st-count f@ ;
: st-sum float+ f@ ;
: st-sumsq 2 floats + f@ ;
: st-mean
dup st-sum st-count f/ ;
: st-variance
dup st-sumsq
dup st-mean fdup f* dup st-count f* f-
st-count f/ ;
: st-stddev
st-variance fsqrt ;
: st-add
dup
1e dup f+! float+... | data = Array(2,4,4,4,5,5,7,9)
For i = 0 To UBound(data)
WScript.StdOut.Write "value = " & data(i) &_
" running sd = " & sd(data,i)
WScript.StdOut.WriteLine
Next
Function sd(arr,n)
mean = 0
variance = 0
For j = 0 To n
mean = mean + arr(j)
Next
mean = mean/(n+1)
For k = 0 To n
variance = variance + ((arr(... |
Keep all operations the same but rewrite the snippet in Go. | : f+! dup f@ f+ f! ;
: st-count f@ ;
: st-sum float+ f@ ;
: st-sumsq 2 floats + f@ ;
: st-mean
dup st-sum st-count f/ ;
: st-variance
dup st-sumsq
dup st-mean fdup f* dup st-count f* f-
st-count f/ ;
: st-stddev
st-variance fsqrt ;
: st-add
dup
1e dup f+! float+... | package main
import (
"fmt"
"math"
)
func newRsdv() func(float64) float64 {
var n, a, q float64
return func(x float64) float64 {
n++
a1 := a+(x-a)/n
q, a = q+(x-a)*(x-a1), a1
return math.Sqrt(q/n)
}
}
func main() {
r := newRsdv()
for _, x := range []float6... |
Can you help me rewrite this code in C# instead of Fortran, keeping it the same logically? | program standard_deviation
implicit none
integer(kind=4), parameter :: dp = kind(0.0d0)
real(kind=dp), dimension(:), allocatable :: vals
integer(kind=4) :: i
real(kind=dp), dimension(8) :: sample_data = (/ 2, 4, 4, 4, 5, 5, 7, 9 /)
do i = lbound(sample_data, 1), ubound(sample_data, 1)
call sample_add... | using System;
using System.Collections.Generic;
using System.Linq;
namespace standardDeviation
{
class Program
{
static void Main(string[] args)
{
List<double> nums = new List<double> { 2, 4, 4, 4, 5, 5, 7, 9 };
for (int i = 1; i <= nums.Count; i++)
... |
Write a version of this Fortran function in C++ with identical behavior. | program standard_deviation
implicit none
integer(kind=4), parameter :: dp = kind(0.0d0)
real(kind=dp), dimension(:), allocatable :: vals
integer(kind=4) :: i
real(kind=dp), dimension(8) :: sample_data = (/ 2, 4, 4, 4, 5, 5, 7, 9 /)
do i = lbound(sample_data, 1), ubound(sample_data, 1)
call sample_add... | #include <assert.h>
#include <cmath>
#include <vector>
#include <iostream>
template<int N> struct MomentsAccumulator_
{
std::vector<double> m_;
MomentsAccumulator_() : m_(N + 1, 0.0) {}
void operator()(double v)
{
double inc = 1.0;
for (auto& mi : m_)
{
mi += inc;
inc *= v;
}
}
};
double Stdev(cons... |
Ensure the translated C code behaves exactly like the original Fortran snippet. | program standard_deviation
implicit none
integer(kind=4), parameter :: dp = kind(0.0d0)
real(kind=dp), dimension(:), allocatable :: vals
integer(kind=4) :: i
real(kind=dp), dimension(8) :: sample_data = (/ 2, 4, 4, 4, 5, 5, 7, 9 /)
do i = lbound(sample_data, 1), ubound(sample_data, 1)
call sample_add... | #include <stdio.h>
#include <stdlib.h>
#include <math.h>
typedef enum Action { STDDEV, MEAN, VAR, COUNT } Action;
typedef struct stat_obj_struct {
double sum, sum2;
size_t num;
Action action;
} sStatObject, *StatObject;
StatObject NewStatObject( Action action )
{
StatObject so;
so = malloc(sizeof(sSta... |
Rewrite the snippet below in Go so it works the same as the original Fortran code. | program standard_deviation
implicit none
integer(kind=4), parameter :: dp = kind(0.0d0)
real(kind=dp), dimension(:), allocatable :: vals
integer(kind=4) :: i
real(kind=dp), dimension(8) :: sample_data = (/ 2, 4, 4, 4, 5, 5, 7, 9 /)
do i = lbound(sample_data, 1), ubound(sample_data, 1)
call sample_add... | package main
import (
"fmt"
"math"
)
func newRsdv() func(float64) float64 {
var n, a, q float64
return func(x float64) float64 {
n++
a1 := a+(x-a)/n
q, a = q+(x-a)*(x-a1), a1
return math.Sqrt(q/n)
}
}
func main() {
r := newRsdv()
for _, x := range []float6... |
Port the provided Fortran code into Java while preserving the original functionality. | program standard_deviation
implicit none
integer(kind=4), parameter :: dp = kind(0.0d0)
real(kind=dp), dimension(:), allocatable :: vals
integer(kind=4) :: i
real(kind=dp), dimension(8) :: sample_data = (/ 2, 4, 4, 4, 5, 5, 7, 9 /)
do i = lbound(sample_data, 1), ubound(sample_data, 1)
call sample_add... | public class StdDev {
int n = 0;
double sum = 0;
double sum2 = 0;
public double sd(double x) {
n++;
sum += x;
sum2 += x*x;
return Math.sqrt(sum2/n - sum*sum/n/n);
}
public static void main(String[] args) {
double[] testData = {2,4,4,4,5,5,7,9};
StdDev sd = new StdDev();
... |
Change the following Fortran code into Python without altering its purpose. | program standard_deviation
implicit none
integer(kind=4), parameter :: dp = kind(0.0d0)
real(kind=dp), dimension(:), allocatable :: vals
integer(kind=4) :: i
real(kind=dp), dimension(8) :: sample_data = (/ 2, 4, 4, 4, 5, 5, 7, 9 /)
do i = lbound(sample_data, 1), ubound(sample_data, 1)
call sample_add... | >>> from math import sqrt
>>> def sd(x):
sd.sum += x
sd.sum2 += x*x
sd.n += 1.0
sum, sum2, n = sd.sum, sd.sum2, sd.n
return sqrt(sum2/n - sum*sum/n/n)
>>> sd.sum = sd.sum2 = sd.n = 0
>>> for value in (2,4,4,4,5,5,7,9):
print (value, sd(value))
(2, 0.0)
(4, 1.0)
(4, 0.94280904158206258... |
Convert this Fortran snippet to VB and keep its semantics consistent. | program standard_deviation
implicit none
integer(kind=4), parameter :: dp = kind(0.0d0)
real(kind=dp), dimension(:), allocatable :: vals
integer(kind=4) :: i
real(kind=dp), dimension(8) :: sample_data = (/ 2, 4, 4, 4, 5, 5, 7, 9 /)
do i = lbound(sample_data, 1), ubound(sample_data, 1)
call sample_add... | data = Array(2,4,4,4,5,5,7,9)
For i = 0 To UBound(data)
WScript.StdOut.Write "value = " & data(i) &_
" running sd = " & sd(data,i)
WScript.StdOut.WriteLine
Next
Function sd(arr,n)
mean = 0
variance = 0
For j = 0 To n
mean = mean + arr(j)
Next
mean = mean/(n+1)
For k = 0 To n
variance = variance + ((arr(... |
Ensure the translated PHP code behaves exactly like the original Fortran snippet. | program standard_deviation
implicit none
integer(kind=4), parameter :: dp = kind(0.0d0)
real(kind=dp), dimension(:), allocatable :: vals
integer(kind=4) :: i
real(kind=dp), dimension(8) :: sample_data = (/ 2, 4, 4, 4, 5, 5, 7, 9 /)
do i = lbound(sample_data, 1), ubound(sample_data, 1)
call sample_add... | <?php
class sdcalc {
private $cnt, $sumup, $square;
function __construct() {
$this->reset();
}
# callable on an instance
function reset() {
$this->cnt=0; $this->sumup=0; $this->square=0;
}
function add($f) {
$this->cnt++;
$this->sumup += $f;
$this->sq... |
Convert the following code from Groovy to C, ensuring the logic remains intact. | List samples = []
def stdDev = { def sample ->
samples << sample
def sum = samples.sum()
def sumSq = samples.sum { it * it }
def count = samples.size()
(sumSq/count - (sum/count)**2)**0.5
}
[2,4,4,4,5,5,7,9].each {
println "${stdDev(it)}"
}
| #include <stdio.h>
#include <stdlib.h>
#include <math.h>
typedef enum Action { STDDEV, MEAN, VAR, COUNT } Action;
typedef struct stat_obj_struct {
double sum, sum2;
size_t num;
Action action;
} sStatObject, *StatObject;
StatObject NewStatObject( Action action )
{
StatObject so;
so = malloc(sizeof(sSta... |
Write the same algorithm in C# as shown in this Groovy implementation. | List samples = []
def stdDev = { def sample ->
samples << sample
def sum = samples.sum()
def sumSq = samples.sum { it * it }
def count = samples.size()
(sumSq/count - (sum/count)**2)**0.5
}
[2,4,4,4,5,5,7,9].each {
println "${stdDev(it)}"
}
| using System;
using System.Collections.Generic;
using System.Linq;
namespace standardDeviation
{
class Program
{
static void Main(string[] args)
{
List<double> nums = new List<double> { 2, 4, 4, 4, 5, 5, 7, 9 };
for (int i = 1; i <= nums.Count; i++)
... |
Port the following code from Groovy to C++ with equivalent syntax and logic. | List samples = []
def stdDev = { def sample ->
samples << sample
def sum = samples.sum()
def sumSq = samples.sum { it * it }
def count = samples.size()
(sumSq/count - (sum/count)**2)**0.5
}
[2,4,4,4,5,5,7,9].each {
println "${stdDev(it)}"
}
| #include <assert.h>
#include <cmath>
#include <vector>
#include <iostream>
template<int N> struct MomentsAccumulator_
{
std::vector<double> m_;
MomentsAccumulator_() : m_(N + 1, 0.0) {}
void operator()(double v)
{
double inc = 1.0;
for (auto& mi : m_)
{
mi += inc;
inc *= v;
}
}
};
double Stdev(cons... |
Preserve the algorithm and functionality while converting the code from Groovy to Java. | List samples = []
def stdDev = { def sample ->
samples << sample
def sum = samples.sum()
def sumSq = samples.sum { it * it }
def count = samples.size()
(sumSq/count - (sum/count)**2)**0.5
}
[2,4,4,4,5,5,7,9].each {
println "${stdDev(it)}"
}
| public class StdDev {
int n = 0;
double sum = 0;
double sum2 = 0;
public double sd(double x) {
n++;
sum += x;
sum2 += x*x;
return Math.sqrt(sum2/n - sum*sum/n/n);
}
public static void main(String[] args) {
double[] testData = {2,4,4,4,5,5,7,9};
StdDev sd = new StdDev();
... |
Change the following Groovy code into Python without altering its purpose. | List samples = []
def stdDev = { def sample ->
samples << sample
def sum = samples.sum()
def sumSq = samples.sum { it * it }
def count = samples.size()
(sumSq/count - (sum/count)**2)**0.5
}
[2,4,4,4,5,5,7,9].each {
println "${stdDev(it)}"
}
| >>> from math import sqrt
>>> def sd(x):
sd.sum += x
sd.sum2 += x*x
sd.n += 1.0
sum, sum2, n = sd.sum, sd.sum2, sd.n
return sqrt(sum2/n - sum*sum/n/n)
>>> sd.sum = sd.sum2 = sd.n = 0
>>> for value in (2,4,4,4,5,5,7,9):
print (value, sd(value))
(2, 0.0)
(4, 1.0)
(4, 0.94280904158206258... |
Generate a VB translation of this Groovy snippet without changing its computational steps. | List samples = []
def stdDev = { def sample ->
samples << sample
def sum = samples.sum()
def sumSq = samples.sum { it * it }
def count = samples.size()
(sumSq/count - (sum/count)**2)**0.5
}
[2,4,4,4,5,5,7,9].each {
println "${stdDev(it)}"
}
| data = Array(2,4,4,4,5,5,7,9)
For i = 0 To UBound(data)
WScript.StdOut.Write "value = " & data(i) &_
" running sd = " & sd(data,i)
WScript.StdOut.WriteLine
Next
Function sd(arr,n)
mean = 0
variance = 0
For j = 0 To n
mean = mean + arr(j)
Next
mean = mean/(n+1)
For k = 0 To n
variance = variance + ((arr(... |
Produce a functionally identical Go code for the snippet given in Groovy. | List samples = []
def stdDev = { def sample ->
samples << sample
def sum = samples.sum()
def sumSq = samples.sum { it * it }
def count = samples.size()
(sumSq/count - (sum/count)**2)**0.5
}
[2,4,4,4,5,5,7,9].each {
println "${stdDev(it)}"
}
| package main
import (
"fmt"
"math"
)
func newRsdv() func(float64) float64 {
var n, a, q float64
return func(x float64) float64 {
n++
a1 := a+(x-a)/n
q, a = q+(x-a)*(x-a1), a1
return math.Sqrt(q/n)
}
}
func main() {
r := newRsdv()
for _, x := range []float6... |
Produce a functionally identical C code for the snippet given in Haskell. |
import Data.List (foldl')
import Data.STRef
import Control.Monad.ST
data Pair a b = Pair !a !b
sumLen :: [Double] -> Pair Double Double
sumLen = fiof2 . foldl' (\(Pair s l) x -> Pair (s+x) (l+1)) (Pair 0.0 0)
where fiof2 (Pair s l) = Pair s (fromIntegral l)
divl :: Pair Double Double -> Double
divl (Pair _ 0.0... | #include <stdio.h>
#include <stdlib.h>
#include <math.h>
typedef enum Action { STDDEV, MEAN, VAR, COUNT } Action;
typedef struct stat_obj_struct {
double sum, sum2;
size_t num;
Action action;
} sStatObject, *StatObject;
StatObject NewStatObject( Action action )
{
StatObject so;
so = malloc(sizeof(sSta... |
Ensure the translated C# code behaves exactly like the original Haskell snippet. |
import Data.List (foldl')
import Data.STRef
import Control.Monad.ST
data Pair a b = Pair !a !b
sumLen :: [Double] -> Pair Double Double
sumLen = fiof2 . foldl' (\(Pair s l) x -> Pair (s+x) (l+1)) (Pair 0.0 0)
where fiof2 (Pair s l) = Pair s (fromIntegral l)
divl :: Pair Double Double -> Double
divl (Pair _ 0.0... | using System;
using System.Collections.Generic;
using System.Linq;
namespace standardDeviation
{
class Program
{
static void Main(string[] args)
{
List<double> nums = new List<double> { 2, 4, 4, 4, 5, 5, 7, 9 };
for (int i = 1; i <= nums.Count; i++)
... |
Produce a language-to-language conversion: from Haskell to C++, same semantics. |
import Data.List (foldl')
import Data.STRef
import Control.Monad.ST
data Pair a b = Pair !a !b
sumLen :: [Double] -> Pair Double Double
sumLen = fiof2 . foldl' (\(Pair s l) x -> Pair (s+x) (l+1)) (Pair 0.0 0)
where fiof2 (Pair s l) = Pair s (fromIntegral l)
divl :: Pair Double Double -> Double
divl (Pair _ 0.0... | #include <assert.h>
#include <cmath>
#include <vector>
#include <iostream>
template<int N> struct MomentsAccumulator_
{
std::vector<double> m_;
MomentsAccumulator_() : m_(N + 1, 0.0) {}
void operator()(double v)
{
double inc = 1.0;
for (auto& mi : m_)
{
mi += inc;
inc *= v;
}
}
};
double Stdev(cons... |
Rewrite the snippet below in Java so it works the same as the original Haskell code. |
import Data.List (foldl')
import Data.STRef
import Control.Monad.ST
data Pair a b = Pair !a !b
sumLen :: [Double] -> Pair Double Double
sumLen = fiof2 . foldl' (\(Pair s l) x -> Pair (s+x) (l+1)) (Pair 0.0 0)
where fiof2 (Pair s l) = Pair s (fromIntegral l)
divl :: Pair Double Double -> Double
divl (Pair _ 0.0... | public class StdDev {
int n = 0;
double sum = 0;
double sum2 = 0;
public double sd(double x) {
n++;
sum += x;
sum2 += x*x;
return Math.sqrt(sum2/n - sum*sum/n/n);
}
public static void main(String[] args) {
double[] testData = {2,4,4,4,5,5,7,9};
StdDev sd = new StdDev();
... |
Keep all operations the same but rewrite the snippet in Python. |
import Data.List (foldl')
import Data.STRef
import Control.Monad.ST
data Pair a b = Pair !a !b
sumLen :: [Double] -> Pair Double Double
sumLen = fiof2 . foldl' (\(Pair s l) x -> Pair (s+x) (l+1)) (Pair 0.0 0)
where fiof2 (Pair s l) = Pair s (fromIntegral l)
divl :: Pair Double Double -> Double
divl (Pair _ 0.0... | >>> from math import sqrt
>>> def sd(x):
sd.sum += x
sd.sum2 += x*x
sd.n += 1.0
sum, sum2, n = sd.sum, sd.sum2, sd.n
return sqrt(sum2/n - sum*sum/n/n)
>>> sd.sum = sd.sum2 = sd.n = 0
>>> for value in (2,4,4,4,5,5,7,9):
print (value, sd(value))
(2, 0.0)
(4, 1.0)
(4, 0.94280904158206258... |
Convert this Haskell block to VB, preserving its control flow and logic. |
import Data.List (foldl')
import Data.STRef
import Control.Monad.ST
data Pair a b = Pair !a !b
sumLen :: [Double] -> Pair Double Double
sumLen = fiof2 . foldl' (\(Pair s l) x -> Pair (s+x) (l+1)) (Pair 0.0 0)
where fiof2 (Pair s l) = Pair s (fromIntegral l)
divl :: Pair Double Double -> Double
divl (Pair _ 0.0... | data = Array(2,4,4,4,5,5,7,9)
For i = 0 To UBound(data)
WScript.StdOut.Write "value = " & data(i) &_
" running sd = " & sd(data,i)
WScript.StdOut.WriteLine
Next
Function sd(arr,n)
mean = 0
variance = 0
For j = 0 To n
mean = mean + arr(j)
Next
mean = mean/(n+1)
For k = 0 To n
variance = variance + ((arr(... |
Can you help me rewrite this code in Go instead of Haskell, keeping it the same logically? |
import Data.List (foldl')
import Data.STRef
import Control.Monad.ST
data Pair a b = Pair !a !b
sumLen :: [Double] -> Pair Double Double
sumLen = fiof2 . foldl' (\(Pair s l) x -> Pair (s+x) (l+1)) (Pair 0.0 0)
where fiof2 (Pair s l) = Pair s (fromIntegral l)
divl :: Pair Double Double -> Double
divl (Pair _ 0.0... | package main
import (
"fmt"
"math"
)
func newRsdv() func(float64) float64 {
var n, a, q float64
return func(x float64) float64 {
n++
a1 := a+(x-a)/n
q, a = q+(x-a)*(x-a1), a1
return math.Sqrt(q/n)
}
}
func main() {
r := newRsdv()
for _, x := range []float6... |
Keep all operations the same but rewrite the snippet in C. | procedure main()
stddev()
every s := stddev(![2,4,4,4,5,5,7,9]) do
write("stddev (so far) := ",s)
end
procedure stddev(x)
static X,sumX,sum2X
if /x then {
X := []
sumX := sum2X := 0.
}
else {
put(X,x)
sumX +:= x
sum2X +:= x^2
return sqrt( (sum2X / *... | #include <stdio.h>
#include <stdlib.h>
#include <math.h>
typedef enum Action { STDDEV, MEAN, VAR, COUNT } Action;
typedef struct stat_obj_struct {
double sum, sum2;
size_t num;
Action action;
} sStatObject, *StatObject;
StatObject NewStatObject( Action action )
{
StatObject so;
so = malloc(sizeof(sSta... |
Change the following Icon code into C# without altering its purpose. | procedure main()
stddev()
every s := stddev(![2,4,4,4,5,5,7,9]) do
write("stddev (so far) := ",s)
end
procedure stddev(x)
static X,sumX,sum2X
if /x then {
X := []
sumX := sum2X := 0.
}
else {
put(X,x)
sumX +:= x
sum2X +:= x^2
return sqrt( (sum2X / *... | using System;
using System.Collections.Generic;
using System.Linq;
namespace standardDeviation
{
class Program
{
static void Main(string[] args)
{
List<double> nums = new List<double> { 2, 4, 4, 4, 5, 5, 7, 9 };
for (int i = 1; i <= nums.Count; i++)
... |
Produce a language-to-language conversion: from Icon to C++, same semantics. | procedure main()
stddev()
every s := stddev(![2,4,4,4,5,5,7,9]) do
write("stddev (so far) := ",s)
end
procedure stddev(x)
static X,sumX,sum2X
if /x then {
X := []
sumX := sum2X := 0.
}
else {
put(X,x)
sumX +:= x
sum2X +:= x^2
return sqrt( (sum2X / *... | #include <assert.h>
#include <cmath>
#include <vector>
#include <iostream>
template<int N> struct MomentsAccumulator_
{
std::vector<double> m_;
MomentsAccumulator_() : m_(N + 1, 0.0) {}
void operator()(double v)
{
double inc = 1.0;
for (auto& mi : m_)
{
mi += inc;
inc *= v;
}
}
};
double Stdev(cons... |
Generate a Java translation of this Icon snippet without changing its computational steps. | procedure main()
stddev()
every s := stddev(![2,4,4,4,5,5,7,9]) do
write("stddev (so far) := ",s)
end
procedure stddev(x)
static X,sumX,sum2X
if /x then {
X := []
sumX := sum2X := 0.
}
else {
put(X,x)
sumX +:= x
sum2X +:= x^2
return sqrt( (sum2X / *... | public class StdDev {
int n = 0;
double sum = 0;
double sum2 = 0;
public double sd(double x) {
n++;
sum += x;
sum2 += x*x;
return Math.sqrt(sum2/n - sum*sum/n/n);
}
public static void main(String[] args) {
double[] testData = {2,4,4,4,5,5,7,9};
StdDev sd = new StdDev();
... |
Can you help me rewrite this code in VB instead of Icon, keeping it the same logically? | procedure main()
stddev()
every s := stddev(![2,4,4,4,5,5,7,9]) do
write("stddev (so far) := ",s)
end
procedure stddev(x)
static X,sumX,sum2X
if /x then {
X := []
sumX := sum2X := 0.
}
else {
put(X,x)
sumX +:= x
sum2X +:= x^2
return sqrt( (sum2X / *... | data = Array(2,4,4,4,5,5,7,9)
For i = 0 To UBound(data)
WScript.StdOut.Write "value = " & data(i) &_
" running sd = " & sd(data,i)
WScript.StdOut.WriteLine
Next
Function sd(arr,n)
mean = 0
variance = 0
For j = 0 To n
mean = mean + arr(j)
Next
mean = mean/(n+1)
For k = 0 To n
variance = variance + ((arr(... |
Convert the following code from Icon to Go, ensuring the logic remains intact. | procedure main()
stddev()
every s := stddev(![2,4,4,4,5,5,7,9]) do
write("stddev (so far) := ",s)
end
procedure stddev(x)
static X,sumX,sum2X
if /x then {
X := []
sumX := sum2X := 0.
}
else {
put(X,x)
sumX +:= x
sum2X +:= x^2
return sqrt( (sum2X / *... | package main
import (
"fmt"
"math"
)
func newRsdv() func(float64) float64 {
var n, a, q float64
return func(x float64) float64 {
n++
a1 := a+(x-a)/n
q, a = q+(x-a)*(x-a1), a1
return math.Sqrt(q/n)
}
}
func main() {
r := newRsdv()
for _, x := range []float6... |
Generate an equivalent C version of this J code. | mean=: +/ % #
dev=: - mean
stddevP=: [: %:@mean *:@dev
stddevP=: [: mean&.:*: dev
stddevP=: %:@(mean@:*: - *:@mean)
stddevP\ 2 4 4 4 5 5 7 9
0 1 0.942809 0.866025 0.979796 1 1.39971 2
| #include <stdio.h>
#include <stdlib.h>
#include <math.h>
typedef enum Action { STDDEV, MEAN, VAR, COUNT } Action;
typedef struct stat_obj_struct {
double sum, sum2;
size_t num;
Action action;
} sStatObject, *StatObject;
StatObject NewStatObject( Action action )
{
StatObject so;
so = malloc(sizeof(sSta... |
Convert the following code from J to C#, ensuring the logic remains intact. | mean=: +/ % #
dev=: - mean
stddevP=: [: %:@mean *:@dev
stddevP=: [: mean&.:*: dev
stddevP=: %:@(mean@:*: - *:@mean)
stddevP\ 2 4 4 4 5 5 7 9
0 1 0.942809 0.866025 0.979796 1 1.39971 2
| using System;
using System.Collections.Generic;
using System.Linq;
namespace standardDeviation
{
class Program
{
static void Main(string[] args)
{
List<double> nums = new List<double> { 2, 4, 4, 4, 5, 5, 7, 9 };
for (int i = 1; i <= nums.Count; i++)
... |
Port the provided J code into C++ while preserving the original functionality. | mean=: +/ % #
dev=: - mean
stddevP=: [: %:@mean *:@dev
stddevP=: [: mean&.:*: dev
stddevP=: %:@(mean@:*: - *:@mean)
stddevP\ 2 4 4 4 5 5 7 9
0 1 0.942809 0.866025 0.979796 1 1.39971 2
| #include <assert.h>
#include <cmath>
#include <vector>
#include <iostream>
template<int N> struct MomentsAccumulator_
{
std::vector<double> m_;
MomentsAccumulator_() : m_(N + 1, 0.0) {}
void operator()(double v)
{
double inc = 1.0;
for (auto& mi : m_)
{
mi += inc;
inc *= v;
}
}
};
double Stdev(cons... |
Rewrite the snippet below in Java so it works the same as the original J code. | mean=: +/ % #
dev=: - mean
stddevP=: [: %:@mean *:@dev
stddevP=: [: mean&.:*: dev
stddevP=: %:@(mean@:*: - *:@mean)
stddevP\ 2 4 4 4 5 5 7 9
0 1 0.942809 0.866025 0.979796 1 1.39971 2
| public class StdDev {
int n = 0;
double sum = 0;
double sum2 = 0;
public double sd(double x) {
n++;
sum += x;
sum2 += x*x;
return Math.sqrt(sum2/n - sum*sum/n/n);
}
public static void main(String[] args) {
double[] testData = {2,4,4,4,5,5,7,9};
StdDev sd = new StdDev();
... |
Please provide an equivalent version of this J code in Python. | mean=: +/ % #
dev=: - mean
stddevP=: [: %:@mean *:@dev
stddevP=: [: mean&.:*: dev
stddevP=: %:@(mean@:*: - *:@mean)
stddevP\ 2 4 4 4 5 5 7 9
0 1 0.942809 0.866025 0.979796 1 1.39971 2
| >>> from math import sqrt
>>> def sd(x):
sd.sum += x
sd.sum2 += x*x
sd.n += 1.0
sum, sum2, n = sd.sum, sd.sum2, sd.n
return sqrt(sum2/n - sum*sum/n/n)
>>> sd.sum = sd.sum2 = sd.n = 0
>>> for value in (2,4,4,4,5,5,7,9):
print (value, sd(value))
(2, 0.0)
(4, 1.0)
(4, 0.94280904158206258... |
Please provide an equivalent version of this J code in VB. | mean=: +/ % #
dev=: - mean
stddevP=: [: %:@mean *:@dev
stddevP=: [: mean&.:*: dev
stddevP=: %:@(mean@:*: - *:@mean)
stddevP\ 2 4 4 4 5 5 7 9
0 1 0.942809 0.866025 0.979796 1 1.39971 2
| data = Array(2,4,4,4,5,5,7,9)
For i = 0 To UBound(data)
WScript.StdOut.Write "value = " & data(i) &_
" running sd = " & sd(data,i)
WScript.StdOut.WriteLine
Next
Function sd(arr,n)
mean = 0
variance = 0
For j = 0 To n
mean = mean + arr(j)
Next
mean = mean/(n+1)
For k = 0 To n
variance = variance + ((arr(... |
Maintain the same structure and functionality when rewriting this code in Go. | mean=: +/ % #
dev=: - mean
stddevP=: [: %:@mean *:@dev
stddevP=: [: mean&.:*: dev
stddevP=: %:@(mean@:*: - *:@mean)
stddevP\ 2 4 4 4 5 5 7 9
0 1 0.942809 0.866025 0.979796 1 1.39971 2
| package main
import (
"fmt"
"math"
)
func newRsdv() func(float64) float64 {
var n, a, q float64
return func(x float64) float64 {
n++
a1 := a+(x-a)/n
q, a = q+(x-a)*(x-a1), a1
return math.Sqrt(q/n)
}
}
func main() {
r := newRsdv()
for _, x := range []float6... |
Change the following Julia code into C without altering its purpose. | function makerunningstd(::Type{T} = Float64) where T
∑x = ∑x² = zero(T)
n = 0
function runningstd(x)
∑x += x
∑x² += x ^ 2
n += 1
s = ∑x² / n - (∑x / n) ^ 2
return s
end
return runningstd
end
test = Float64[2, 4, 4, 4, 5, 5, 7, 9]
rstd = makerunningstd()
... | #include <stdio.h>
#include <stdlib.h>
#include <math.h>
typedef enum Action { STDDEV, MEAN, VAR, COUNT } Action;
typedef struct stat_obj_struct {
double sum, sum2;
size_t num;
Action action;
} sStatObject, *StatObject;
StatObject NewStatObject( Action action )
{
StatObject so;
so = malloc(sizeof(sSta... |
Port the following code from Julia to C# with equivalent syntax and logic. | function makerunningstd(::Type{T} = Float64) where T
∑x = ∑x² = zero(T)
n = 0
function runningstd(x)
∑x += x
∑x² += x ^ 2
n += 1
s = ∑x² / n - (∑x / n) ^ 2
return s
end
return runningstd
end
test = Float64[2, 4, 4, 4, 5, 5, 7, 9]
rstd = makerunningstd()
... | using System;
using System.Collections.Generic;
using System.Linq;
namespace standardDeviation
{
class Program
{
static void Main(string[] args)
{
List<double> nums = new List<double> { 2, 4, 4, 4, 5, 5, 7, 9 };
for (int i = 1; i <= nums.Count; i++)
... |
Transform the following Julia implementation into C++, maintaining the same output and logic. | function makerunningstd(::Type{T} = Float64) where T
∑x = ∑x² = zero(T)
n = 0
function runningstd(x)
∑x += x
∑x² += x ^ 2
n += 1
s = ∑x² / n - (∑x / n) ^ 2
return s
end
return runningstd
end
test = Float64[2, 4, 4, 4, 5, 5, 7, 9]
rstd = makerunningstd()
... | #include <assert.h>
#include <cmath>
#include <vector>
#include <iostream>
template<int N> struct MomentsAccumulator_
{
std::vector<double> m_;
MomentsAccumulator_() : m_(N + 1, 0.0) {}
void operator()(double v)
{
double inc = 1.0;
for (auto& mi : m_)
{
mi += inc;
inc *= v;
}
}
};
double Stdev(cons... |
Change the programming language of this snippet from Julia to Java without modifying what it does. | function makerunningstd(::Type{T} = Float64) where T
∑x = ∑x² = zero(T)
n = 0
function runningstd(x)
∑x += x
∑x² += x ^ 2
n += 1
s = ∑x² / n - (∑x / n) ^ 2
return s
end
return runningstd
end
test = Float64[2, 4, 4, 4, 5, 5, 7, 9]
rstd = makerunningstd()
... | public class StdDev {
int n = 0;
double sum = 0;
double sum2 = 0;
public double sd(double x) {
n++;
sum += x;
sum2 += x*x;
return Math.sqrt(sum2/n - sum*sum/n/n);
}
public static void main(String[] args) {
double[] testData = {2,4,4,4,5,5,7,9};
StdDev sd = new StdDev();
... |
Maintain the same structure and functionality when rewriting this code in Python. | function makerunningstd(::Type{T} = Float64) where T
∑x = ∑x² = zero(T)
n = 0
function runningstd(x)
∑x += x
∑x² += x ^ 2
n += 1
s = ∑x² / n - (∑x / n) ^ 2
return s
end
return runningstd
end
test = Float64[2, 4, 4, 4, 5, 5, 7, 9]
rstd = makerunningstd()
... | >>> from math import sqrt
>>> def sd(x):
sd.sum += x
sd.sum2 += x*x
sd.n += 1.0
sum, sum2, n = sd.sum, sd.sum2, sd.n
return sqrt(sum2/n - sum*sum/n/n)
>>> sd.sum = sd.sum2 = sd.n = 0
>>> for value in (2,4,4,4,5,5,7,9):
print (value, sd(value))
(2, 0.0)
(4, 1.0)
(4, 0.94280904158206258... |
Write a version of this Julia function in VB with identical behavior. | function makerunningstd(::Type{T} = Float64) where T
∑x = ∑x² = zero(T)
n = 0
function runningstd(x)
∑x += x
∑x² += x ^ 2
n += 1
s = ∑x² / n - (∑x / n) ^ 2
return s
end
return runningstd
end
test = Float64[2, 4, 4, 4, 5, 5, 7, 9]
rstd = makerunningstd()
... | data = Array(2,4,4,4,5,5,7,9)
For i = 0 To UBound(data)
WScript.StdOut.Write "value = " & data(i) &_
" running sd = " & sd(data,i)
WScript.StdOut.WriteLine
Next
Function sd(arr,n)
mean = 0
variance = 0
For j = 0 To n
mean = mean + arr(j)
Next
mean = mean/(n+1)
For k = 0 To n
variance = variance + ((arr(... |
Please provide an equivalent version of this Julia code in Go. | function makerunningstd(::Type{T} = Float64) where T
∑x = ∑x² = zero(T)
n = 0
function runningstd(x)
∑x += x
∑x² += x ^ 2
n += 1
s = ∑x² / n - (∑x / n) ^ 2
return s
end
return runningstd
end
test = Float64[2, 4, 4, 4, 5, 5, 7, 9]
rstd = makerunningstd()
... | package main
import (
"fmt"
"math"
)
func newRsdv() func(float64) float64 {
var n, a, q float64
return func(x float64) float64 {
n++
a1 := a+(x-a)/n
q, a = q+(x-a)*(x-a1), a1
return math.Sqrt(q/n)
}
}
func main() {
r := newRsdv()
for _, x := range []float6... |
Transform the following Lua implementation into C, maintaining the same output and logic. | function stdev()
local sum, sumsq, k = 0,0,0
return function(n)
sum, sumsq, k = sum + n, sumsq + n^2, k+1
return math.sqrt((sumsq / k) - (sum/k)^2)
end
end
ldev = stdev()
for i, v in ipairs{2,4,4,4,5,5,7,9} do
print(ldev(v))
end
| #include <stdio.h>
#include <stdlib.h>
#include <math.h>
typedef enum Action { STDDEV, MEAN, VAR, COUNT } Action;
typedef struct stat_obj_struct {
double sum, sum2;
size_t num;
Action action;
} sStatObject, *StatObject;
StatObject NewStatObject( Action action )
{
StatObject so;
so = malloc(sizeof(sSta... |
Preserve the algorithm and functionality while converting the code from Lua to C#. | function stdev()
local sum, sumsq, k = 0,0,0
return function(n)
sum, sumsq, k = sum + n, sumsq + n^2, k+1
return math.sqrt((sumsq / k) - (sum/k)^2)
end
end
ldev = stdev()
for i, v in ipairs{2,4,4,4,5,5,7,9} do
print(ldev(v))
end
| using System;
using System.Collections.Generic;
using System.Linq;
namespace standardDeviation
{
class Program
{
static void Main(string[] args)
{
List<double> nums = new List<double> { 2, 4, 4, 4, 5, 5, 7, 9 };
for (int i = 1; i <= nums.Count; i++)
... |
Transform the following Lua implementation into C++, maintaining the same output and logic. | function stdev()
local sum, sumsq, k = 0,0,0
return function(n)
sum, sumsq, k = sum + n, sumsq + n^2, k+1
return math.sqrt((sumsq / k) - (sum/k)^2)
end
end
ldev = stdev()
for i, v in ipairs{2,4,4,4,5,5,7,9} do
print(ldev(v))
end
| #include <assert.h>
#include <cmath>
#include <vector>
#include <iostream>
template<int N> struct MomentsAccumulator_
{
std::vector<double> m_;
MomentsAccumulator_() : m_(N + 1, 0.0) {}
void operator()(double v)
{
double inc = 1.0;
for (auto& mi : m_)
{
mi += inc;
inc *= v;
}
}
};
double Stdev(cons... |
Write the same algorithm in Java as shown in this Lua implementation. | function stdev()
local sum, sumsq, k = 0,0,0
return function(n)
sum, sumsq, k = sum + n, sumsq + n^2, k+1
return math.sqrt((sumsq / k) - (sum/k)^2)
end
end
ldev = stdev()
for i, v in ipairs{2,4,4,4,5,5,7,9} do
print(ldev(v))
end
| public class StdDev {
int n = 0;
double sum = 0;
double sum2 = 0;
public double sd(double x) {
n++;
sum += x;
sum2 += x*x;
return Math.sqrt(sum2/n - sum*sum/n/n);
}
public static void main(String[] args) {
double[] testData = {2,4,4,4,5,5,7,9};
StdDev sd = new StdDev();
... |
Translate this program into Python but keep the logic exactly as in Lua. | function stdev()
local sum, sumsq, k = 0,0,0
return function(n)
sum, sumsq, k = sum + n, sumsq + n^2, k+1
return math.sqrt((sumsq / k) - (sum/k)^2)
end
end
ldev = stdev()
for i, v in ipairs{2,4,4,4,5,5,7,9} do
print(ldev(v))
end
| >>> from math import sqrt
>>> def sd(x):
sd.sum += x
sd.sum2 += x*x
sd.n += 1.0
sum, sum2, n = sd.sum, sd.sum2, sd.n
return sqrt(sum2/n - sum*sum/n/n)
>>> sd.sum = sd.sum2 = sd.n = 0
>>> for value in (2,4,4,4,5,5,7,9):
print (value, sd(value))
(2, 0.0)
(4, 1.0)
(4, 0.94280904158206258... |
Convert the following code from Lua to VB, ensuring the logic remains intact. | function stdev()
local sum, sumsq, k = 0,0,0
return function(n)
sum, sumsq, k = sum + n, sumsq + n^2, k+1
return math.sqrt((sumsq / k) - (sum/k)^2)
end
end
ldev = stdev()
for i, v in ipairs{2,4,4,4,5,5,7,9} do
print(ldev(v))
end
| data = Array(2,4,4,4,5,5,7,9)
For i = 0 To UBound(data)
WScript.StdOut.Write "value = " & data(i) &_
" running sd = " & sd(data,i)
WScript.StdOut.WriteLine
Next
Function sd(arr,n)
mean = 0
variance = 0
For j = 0 To n
mean = mean + arr(j)
Next
mean = mean/(n+1)
For k = 0 To n
variance = variance + ((arr(... |
Convert the following code from Lua to Go, ensuring the logic remains intact. | function stdev()
local sum, sumsq, k = 0,0,0
return function(n)
sum, sumsq, k = sum + n, sumsq + n^2, k+1
return math.sqrt((sumsq / k) - (sum/k)^2)
end
end
ldev = stdev()
for i, v in ipairs{2,4,4,4,5,5,7,9} do
print(ldev(v))
end
| package main
import (
"fmt"
"math"
)
func newRsdv() func(float64) float64 {
var n, a, q float64
return func(x float64) float64 {
n++
a1 := a+(x-a)/n
q, a = q+(x-a)*(x-a1), a1
return math.Sqrt(q/n)
}
}
func main() {
r := newRsdv()
for _, x := range []float6... |
Port the following code from Mathematica to C with equivalent syntax and logic. | runningSTDDev[n_] := (If[Not[ValueQ[$Data]], $Data = {}];StandardDeviation[AppendTo[$Data, n]])
| #include <stdio.h>
#include <stdlib.h>
#include <math.h>
typedef enum Action { STDDEV, MEAN, VAR, COUNT } Action;
typedef struct stat_obj_struct {
double sum, sum2;
size_t num;
Action action;
} sStatObject, *StatObject;
StatObject NewStatObject( Action action )
{
StatObject so;
so = malloc(sizeof(sSta... |
Produce a language-to-language conversion: from Mathematica to C#, same semantics. | runningSTDDev[n_] := (If[Not[ValueQ[$Data]], $Data = {}];StandardDeviation[AppendTo[$Data, n]])
| using System;
using System.Collections.Generic;
using System.Linq;
namespace standardDeviation
{
class Program
{
static void Main(string[] args)
{
List<double> nums = new List<double> { 2, 4, 4, 4, 5, 5, 7, 9 };
for (int i = 1; i <= nums.Count; i++)
... |
Write the same algorithm in C++ as shown in this Mathematica implementation. | runningSTDDev[n_] := (If[Not[ValueQ[$Data]], $Data = {}];StandardDeviation[AppendTo[$Data, n]])
| #include <assert.h>
#include <cmath>
#include <vector>
#include <iostream>
template<int N> struct MomentsAccumulator_
{
std::vector<double> m_;
MomentsAccumulator_() : m_(N + 1, 0.0) {}
void operator()(double v)
{
double inc = 1.0;
for (auto& mi : m_)
{
mi += inc;
inc *= v;
}
}
};
double Stdev(cons... |
Translate the given Mathematica code snippet into Java without altering its behavior. | runningSTDDev[n_] := (If[Not[ValueQ[$Data]], $Data = {}];StandardDeviation[AppendTo[$Data, n]])
| public class StdDev {
int n = 0;
double sum = 0;
double sum2 = 0;
public double sd(double x) {
n++;
sum += x;
sum2 += x*x;
return Math.sqrt(sum2/n - sum*sum/n/n);
}
public static void main(String[] args) {
double[] testData = {2,4,4,4,5,5,7,9};
StdDev sd = new StdDev();
... |
Convert the following code from Mathematica to Python, ensuring the logic remains intact. | runningSTDDev[n_] := (If[Not[ValueQ[$Data]], $Data = {}];StandardDeviation[AppendTo[$Data, n]])
| >>> from math import sqrt
>>> def sd(x):
sd.sum += x
sd.sum2 += x*x
sd.n += 1.0
sum, sum2, n = sd.sum, sd.sum2, sd.n
return sqrt(sum2/n - sum*sum/n/n)
>>> sd.sum = sd.sum2 = sd.n = 0
>>> for value in (2,4,4,4,5,5,7,9):
print (value, sd(value))
(2, 0.0)
(4, 1.0)
(4, 0.94280904158206258... |
Change the following Mathematica code into VB without altering its purpose. | runningSTDDev[n_] := (If[Not[ValueQ[$Data]], $Data = {}];StandardDeviation[AppendTo[$Data, n]])
| data = Array(2,4,4,4,5,5,7,9)
For i = 0 To UBound(data)
WScript.StdOut.Write "value = " & data(i) &_
" running sd = " & sd(data,i)
WScript.StdOut.WriteLine
Next
Function sd(arr,n)
mean = 0
variance = 0
For j = 0 To n
mean = mean + arr(j)
Next
mean = mean/(n+1)
For k = 0 To n
variance = variance + ((arr(... |
Produce a functionally identical Go code for the snippet given in Mathematica. | runningSTDDev[n_] := (If[Not[ValueQ[$Data]], $Data = {}];StandardDeviation[AppendTo[$Data, n]])
| package main
import (
"fmt"
"math"
)
func newRsdv() func(float64) float64 {
var n, a, q float64
return func(x float64) float64 {
n++
a1 := a+(x-a)/n
q, a = q+(x-a)*(x-a1), a1
return math.Sqrt(q/n)
}
}
func main() {
r := newRsdv()
for _, x := range []float6... |
Ensure the translated C code behaves exactly like the original MATLAB snippet. | x = [2,4,4,4,5,5,7,9];
n = length (x);
m = mean (x);
x2 = mean (x .* x);
dev= sqrt (x2 - m * m)
dev = 2
| #include <stdio.h>
#include <stdlib.h>
#include <math.h>
typedef enum Action { STDDEV, MEAN, VAR, COUNT } Action;
typedef struct stat_obj_struct {
double sum, sum2;
size_t num;
Action action;
} sStatObject, *StatObject;
StatObject NewStatObject( Action action )
{
StatObject so;
so = malloc(sizeof(sSta... |
Change the following MATLAB code into C# without altering its purpose. | x = [2,4,4,4,5,5,7,9];
n = length (x);
m = mean (x);
x2 = mean (x .* x);
dev= sqrt (x2 - m * m)
dev = 2
| using System;
using System.Collections.Generic;
using System.Linq;
namespace standardDeviation
{
class Program
{
static void Main(string[] args)
{
List<double> nums = new List<double> { 2, 4, 4, 4, 5, 5, 7, 9 };
for (int i = 1; i <= nums.Count; i++)
... |
Change the programming language of this snippet from MATLAB to C++ without modifying what it does. | x = [2,4,4,4,5,5,7,9];
n = length (x);
m = mean (x);
x2 = mean (x .* x);
dev= sqrt (x2 - m * m)
dev = 2
| #include <assert.h>
#include <cmath>
#include <vector>
#include <iostream>
template<int N> struct MomentsAccumulator_
{
std::vector<double> m_;
MomentsAccumulator_() : m_(N + 1, 0.0) {}
void operator()(double v)
{
double inc = 1.0;
for (auto& mi : m_)
{
mi += inc;
inc *= v;
}
}
};
double Stdev(cons... |
Translate the given MATLAB code snippet into Java without altering its behavior. | x = [2,4,4,4,5,5,7,9];
n = length (x);
m = mean (x);
x2 = mean (x .* x);
dev= sqrt (x2 - m * m)
dev = 2
| public class StdDev {
int n = 0;
double sum = 0;
double sum2 = 0;
public double sd(double x) {
n++;
sum += x;
sum2 += x*x;
return Math.sqrt(sum2/n - sum*sum/n/n);
}
public static void main(String[] args) {
double[] testData = {2,4,4,4,5,5,7,9};
StdDev sd = new StdDev();
... |
Write the same code in Python as shown below in MATLAB. | x = [2,4,4,4,5,5,7,9];
n = length (x);
m = mean (x);
x2 = mean (x .* x);
dev= sqrt (x2 - m * m)
dev = 2
| >>> from math import sqrt
>>> def sd(x):
sd.sum += x
sd.sum2 += x*x
sd.n += 1.0
sum, sum2, n = sd.sum, sd.sum2, sd.n
return sqrt(sum2/n - sum*sum/n/n)
>>> sd.sum = sd.sum2 = sd.n = 0
>>> for value in (2,4,4,4,5,5,7,9):
print (value, sd(value))
(2, 0.0)
(4, 1.0)
(4, 0.94280904158206258... |
Convert this MATLAB block to Go, preserving its control flow and logic. | x = [2,4,4,4,5,5,7,9];
n = length (x);
m = mean (x);
x2 = mean (x .* x);
dev= sqrt (x2 - m * m)
dev = 2
| package main
import (
"fmt"
"math"
)
func newRsdv() func(float64) float64 {
var n, a, q float64
return func(x float64) float64 {
n++
a1 := a+(x-a)/n
q, a = q+(x-a)*(x-a1), a1
return math.Sqrt(q/n)
}
}
func main() {
r := newRsdv()
for _, x := range []float6... |
Preserve the algorithm and functionality while converting the code from Nim to C. | import math, strutils
var sdSum, sdSum2, sdN = 0.0
proc sd(x: float): float =
sdN += 1
sdSum += x
sdSum2 += x * x
sqrt(sdSum2 / sdN - sdSum * sdSum / (sdN * sdN))
for value in [float 2,4,4,4,5,5,7,9]:
echo value, " ", formatFloat(sd(value), precision = -1)
| #include <stdio.h>
#include <stdlib.h>
#include <math.h>
typedef enum Action { STDDEV, MEAN, VAR, COUNT } Action;
typedef struct stat_obj_struct {
double sum, sum2;
size_t num;
Action action;
} sStatObject, *StatObject;
StatObject NewStatObject( Action action )
{
StatObject so;
so = malloc(sizeof(sSta... |
Maintain the same structure and functionality when rewriting this code in C#. | import math, strutils
var sdSum, sdSum2, sdN = 0.0
proc sd(x: float): float =
sdN += 1
sdSum += x
sdSum2 += x * x
sqrt(sdSum2 / sdN - sdSum * sdSum / (sdN * sdN))
for value in [float 2,4,4,4,5,5,7,9]:
echo value, " ", formatFloat(sd(value), precision = -1)
| using System;
using System.Collections.Generic;
using System.Linq;
namespace standardDeviation
{
class Program
{
static void Main(string[] args)
{
List<double> nums = new List<double> { 2, 4, 4, 4, 5, 5, 7, 9 };
for (int i = 1; i <= nums.Count; i++)
... |
Rewrite the snippet below in C++ so it works the same as the original Nim code. | import math, strutils
var sdSum, sdSum2, sdN = 0.0
proc sd(x: float): float =
sdN += 1
sdSum += x
sdSum2 += x * x
sqrt(sdSum2 / sdN - sdSum * sdSum / (sdN * sdN))
for value in [float 2,4,4,4,5,5,7,9]:
echo value, " ", formatFloat(sd(value), precision = -1)
| #include <assert.h>
#include <cmath>
#include <vector>
#include <iostream>
template<int N> struct MomentsAccumulator_
{
std::vector<double> m_;
MomentsAccumulator_() : m_(N + 1, 0.0) {}
void operator()(double v)
{
double inc = 1.0;
for (auto& mi : m_)
{
mi += inc;
inc *= v;
}
}
};
double Stdev(cons... |
Generate a Java translation of this Nim snippet without changing its computational steps. | import math, strutils
var sdSum, sdSum2, sdN = 0.0
proc sd(x: float): float =
sdN += 1
sdSum += x
sdSum2 += x * x
sqrt(sdSum2 / sdN - sdSum * sdSum / (sdN * sdN))
for value in [float 2,4,4,4,5,5,7,9]:
echo value, " ", formatFloat(sd(value), precision = -1)
| public class StdDev {
int n = 0;
double sum = 0;
double sum2 = 0;
public double sd(double x) {
n++;
sum += x;
sum2 += x*x;
return Math.sqrt(sum2/n - sum*sum/n/n);
}
public static void main(String[] args) {
double[] testData = {2,4,4,4,5,5,7,9};
StdDev sd = new StdDev();
... |
Convert the following code from Nim to Python, ensuring the logic remains intact. | import math, strutils
var sdSum, sdSum2, sdN = 0.0
proc sd(x: float): float =
sdN += 1
sdSum += x
sdSum2 += x * x
sqrt(sdSum2 / sdN - sdSum * sdSum / (sdN * sdN))
for value in [float 2,4,4,4,5,5,7,9]:
echo value, " ", formatFloat(sd(value), precision = -1)
| >>> from math import sqrt
>>> def sd(x):
sd.sum += x
sd.sum2 += x*x
sd.n += 1.0
sum, sum2, n = sd.sum, sd.sum2, sd.n
return sqrt(sum2/n - sum*sum/n/n)
>>> sd.sum = sd.sum2 = sd.n = 0
>>> for value in (2,4,4,4,5,5,7,9):
print (value, sd(value))
(2, 0.0)
(4, 1.0)
(4, 0.94280904158206258... |
Generate a VB translation of this Nim snippet without changing its computational steps. | import math, strutils
var sdSum, sdSum2, sdN = 0.0
proc sd(x: float): float =
sdN += 1
sdSum += x
sdSum2 += x * x
sqrt(sdSum2 / sdN - sdSum * sdSum / (sdN * sdN))
for value in [float 2,4,4,4,5,5,7,9]:
echo value, " ", formatFloat(sd(value), precision = -1)
| data = Array(2,4,4,4,5,5,7,9)
For i = 0 To UBound(data)
WScript.StdOut.Write "value = " & data(i) &_
" running sd = " & sd(data,i)
WScript.StdOut.WriteLine
Next
Function sd(arr,n)
mean = 0
variance = 0
For j = 0 To n
mean = mean + arr(j)
Next
mean = mean/(n+1)
For k = 0 To n
variance = variance + ((arr(... |
Write the same code in Go as shown below in Nim. | import math, strutils
var sdSum, sdSum2, sdN = 0.0
proc sd(x: float): float =
sdN += 1
sdSum += x
sdSum2 += x * x
sqrt(sdSum2 / sdN - sdSum * sdSum / (sdN * sdN))
for value in [float 2,4,4,4,5,5,7,9]:
echo value, " ", formatFloat(sd(value), precision = -1)
| package main
import (
"fmt"
"math"
)
func newRsdv() func(float64) float64 {
var n, a, q float64
return func(x float64) float64 {
n++
a1 := a+(x-a)/n
q, a = q+(x-a)*(x-a1), a1
return math.Sqrt(q/n)
}
}
func main() {
r := newRsdv()
for _, x := range []float6... |
Convert this OCaml snippet to C and keep its semantics consistent. | let sqr x = x *. x
let stddev l =
let n, sx, sx2 =
List.fold_left
(fun (n, sx, sx2) x -> succ n, sx +. x, sx2 +. sqr x)
(0, 0., 0.) l
in
sqrt ((sx2 -. sqr sx /. float n) /. float n)
let _ =
let l = [ 2.;4.;4.;4.;5.;5.;7.;9. ] in
Printf.printf "List: ";
List.iter (Printf.printf "%g ") l;
... | #include <stdio.h>
#include <stdlib.h>
#include <math.h>
typedef enum Action { STDDEV, MEAN, VAR, COUNT } Action;
typedef struct stat_obj_struct {
double sum, sum2;
size_t num;
Action action;
} sStatObject, *StatObject;
StatObject NewStatObject( Action action )
{
StatObject so;
so = malloc(sizeof(sSta... |
Keep all operations the same but rewrite the snippet in C#. | let sqr x = x *. x
let stddev l =
let n, sx, sx2 =
List.fold_left
(fun (n, sx, sx2) x -> succ n, sx +. x, sx2 +. sqr x)
(0, 0., 0.) l
in
sqrt ((sx2 -. sqr sx /. float n) /. float n)
let _ =
let l = [ 2.;4.;4.;4.;5.;5.;7.;9. ] in
Printf.printf "List: ";
List.iter (Printf.printf "%g ") l;
... | using System;
using System.Collections.Generic;
using System.Linq;
namespace standardDeviation
{
class Program
{
static void Main(string[] args)
{
List<double> nums = new List<double> { 2, 4, 4, 4, 5, 5, 7, 9 };
for (int i = 1; i <= nums.Count; i++)
... |
Rewrite the snippet below in C++ so it works the same as the original OCaml code. | let sqr x = x *. x
let stddev l =
let n, sx, sx2 =
List.fold_left
(fun (n, sx, sx2) x -> succ n, sx +. x, sx2 +. sqr x)
(0, 0., 0.) l
in
sqrt ((sx2 -. sqr sx /. float n) /. float n)
let _ =
let l = [ 2.;4.;4.;4.;5.;5.;7.;9. ] in
Printf.printf "List: ";
List.iter (Printf.printf "%g ") l;
... | #include <assert.h>
#include <cmath>
#include <vector>
#include <iostream>
template<int N> struct MomentsAccumulator_
{
std::vector<double> m_;
MomentsAccumulator_() : m_(N + 1, 0.0) {}
void operator()(double v)
{
double inc = 1.0;
for (auto& mi : m_)
{
mi += inc;
inc *= v;
}
}
};
double Stdev(cons... |
Maintain the same structure and functionality when rewriting this code in Java. | let sqr x = x *. x
let stddev l =
let n, sx, sx2 =
List.fold_left
(fun (n, sx, sx2) x -> succ n, sx +. x, sx2 +. sqr x)
(0, 0., 0.) l
in
sqrt ((sx2 -. sqr sx /. float n) /. float n)
let _ =
let l = [ 2.;4.;4.;4.;5.;5.;7.;9. ] in
Printf.printf "List: ";
List.iter (Printf.printf "%g ") l;
... | public class StdDev {
int n = 0;
double sum = 0;
double sum2 = 0;
public double sd(double x) {
n++;
sum += x;
sum2 += x*x;
return Math.sqrt(sum2/n - sum*sum/n/n);
}
public static void main(String[] args) {
double[] testData = {2,4,4,4,5,5,7,9};
StdDev sd = new StdDev();
... |
Produce a language-to-language conversion: from OCaml to Python, same semantics. | let sqr x = x *. x
let stddev l =
let n, sx, sx2 =
List.fold_left
(fun (n, sx, sx2) x -> succ n, sx +. x, sx2 +. sqr x)
(0, 0., 0.) l
in
sqrt ((sx2 -. sqr sx /. float n) /. float n)
let _ =
let l = [ 2.;4.;4.;4.;5.;5.;7.;9. ] in
Printf.printf "List: ";
List.iter (Printf.printf "%g ") l;
... | >>> from math import sqrt
>>> def sd(x):
sd.sum += x
sd.sum2 += x*x
sd.n += 1.0
sum, sum2, n = sd.sum, sd.sum2, sd.n
return sqrt(sum2/n - sum*sum/n/n)
>>> sd.sum = sd.sum2 = sd.n = 0
>>> for value in (2,4,4,4,5,5,7,9):
print (value, sd(value))
(2, 0.0)
(4, 1.0)
(4, 0.94280904158206258... |
Translate the given OCaml code snippet into VB without altering its behavior. | let sqr x = x *. x
let stddev l =
let n, sx, sx2 =
List.fold_left
(fun (n, sx, sx2) x -> succ n, sx +. x, sx2 +. sqr x)
(0, 0., 0.) l
in
sqrt ((sx2 -. sqr sx /. float n) /. float n)
let _ =
let l = [ 2.;4.;4.;4.;5.;5.;7.;9. ] in
Printf.printf "List: ";
List.iter (Printf.printf "%g ") l;
... | data = Array(2,4,4,4,5,5,7,9)
For i = 0 To UBound(data)
WScript.StdOut.Write "value = " & data(i) &_
" running sd = " & sd(data,i)
WScript.StdOut.WriteLine
Next
Function sd(arr,n)
mean = 0
variance = 0
For j = 0 To n
mean = mean + arr(j)
Next
mean = mean/(n+1)
For k = 0 To n
variance = variance + ((arr(... |
Please provide an equivalent version of this OCaml code in Go. | let sqr x = x *. x
let stddev l =
let n, sx, sx2 =
List.fold_left
(fun (n, sx, sx2) x -> succ n, sx +. x, sx2 +. sqr x)
(0, 0., 0.) l
in
sqrt ((sx2 -. sqr sx /. float n) /. float n)
let _ =
let l = [ 2.;4.;4.;4.;5.;5.;7.;9. ] in
Printf.printf "List: ";
List.iter (Printf.printf "%g ") l;
... | package main
import (
"fmt"
"math"
)
func newRsdv() func(float64) float64 {
var n, a, q float64
return func(x float64) float64 {
n++
a1 := a+(x-a)/n
q, a = q+(x-a)*(x-a1), a1
return math.Sqrt(q/n)
}
}
func main() {
r := newRsdv()
for _, x := range []float6... |
Translate the given Pascal code snippet into C without altering its behavior. | program stddev;
uses math;
const
n=8;
var
arr: array[1..n] of real =(2,4,4,4,5,5,7,9);
function stddev(n: integer): real;
var
i: integer;
s1,s2,variance,x: real;
begin
for i:=1 to n do
begin
x:=arr[i];
s1:=s1+power(x,2);
s2:=s2+x
end;
variance:=((n*s1)-(power(s2,2)))/(power(n... | #include <stdio.h>
#include <stdlib.h>
#include <math.h>
typedef enum Action { STDDEV, MEAN, VAR, COUNT } Action;
typedef struct stat_obj_struct {
double sum, sum2;
size_t num;
Action action;
} sStatObject, *StatObject;
StatObject NewStatObject( Action action )
{
StatObject so;
so = malloc(sizeof(sSta... |
Convert the following code from Pascal to C#, ensuring the logic remains intact. | program stddev;
uses math;
const
n=8;
var
arr: array[1..n] of real =(2,4,4,4,5,5,7,9);
function stddev(n: integer): real;
var
i: integer;
s1,s2,variance,x: real;
begin
for i:=1 to n do
begin
x:=arr[i];
s1:=s1+power(x,2);
s2:=s2+x
end;
variance:=((n*s1)-(power(s2,2)))/(power(n... | using System;
using System.Collections.Generic;
using System.Linq;
namespace standardDeviation
{
class Program
{
static void Main(string[] args)
{
List<double> nums = new List<double> { 2, 4, 4, 4, 5, 5, 7, 9 };
for (int i = 1; i <= nums.Count; i++)
... |
Port the following code from Pascal to C++ with equivalent syntax and logic. | program stddev;
uses math;
const
n=8;
var
arr: array[1..n] of real =(2,4,4,4,5,5,7,9);
function stddev(n: integer): real;
var
i: integer;
s1,s2,variance,x: real;
begin
for i:=1 to n do
begin
x:=arr[i];
s1:=s1+power(x,2);
s2:=s2+x
end;
variance:=((n*s1)-(power(s2,2)))/(power(n... | #include <assert.h>
#include <cmath>
#include <vector>
#include <iostream>
template<int N> struct MomentsAccumulator_
{
std::vector<double> m_;
MomentsAccumulator_() : m_(N + 1, 0.0) {}
void operator()(double v)
{
double inc = 1.0;
for (auto& mi : m_)
{
mi += inc;
inc *= v;
}
}
};
double Stdev(cons... |
Convert the following code from Pascal to Java, ensuring the logic remains intact. | program stddev;
uses math;
const
n=8;
var
arr: array[1..n] of real =(2,4,4,4,5,5,7,9);
function stddev(n: integer): real;
var
i: integer;
s1,s2,variance,x: real;
begin
for i:=1 to n do
begin
x:=arr[i];
s1:=s1+power(x,2);
s2:=s2+x
end;
variance:=((n*s1)-(power(s2,2)))/(power(n... | public class StdDev {
int n = 0;
double sum = 0;
double sum2 = 0;
public double sd(double x) {
n++;
sum += x;
sum2 += x*x;
return Math.sqrt(sum2/n - sum*sum/n/n);
}
public static void main(String[] args) {
double[] testData = {2,4,4,4,5,5,7,9};
StdDev sd = new StdDev();
... |
Write the same algorithm in Python as shown in this Pascal implementation. | program stddev;
uses math;
const
n=8;
var
arr: array[1..n] of real =(2,4,4,4,5,5,7,9);
function stddev(n: integer): real;
var
i: integer;
s1,s2,variance,x: real;
begin
for i:=1 to n do
begin
x:=arr[i];
s1:=s1+power(x,2);
s2:=s2+x
end;
variance:=((n*s1)-(power(s2,2)))/(power(n... | >>> from math import sqrt
>>> def sd(x):
sd.sum += x
sd.sum2 += x*x
sd.n += 1.0
sum, sum2, n = sd.sum, sd.sum2, sd.n
return sqrt(sum2/n - sum*sum/n/n)
>>> sd.sum = sd.sum2 = sd.n = 0
>>> for value in (2,4,4,4,5,5,7,9):
print (value, sd(value))
(2, 0.0)
(4, 1.0)
(4, 0.94280904158206258... |
Port the following code from Pascal to VB with equivalent syntax and logic. | program stddev;
uses math;
const
n=8;
var
arr: array[1..n] of real =(2,4,4,4,5,5,7,9);
function stddev(n: integer): real;
var
i: integer;
s1,s2,variance,x: real;
begin
for i:=1 to n do
begin
x:=arr[i];
s1:=s1+power(x,2);
s2:=s2+x
end;
variance:=((n*s1)-(power(s2,2)))/(power(n... | data = Array(2,4,4,4,5,5,7,9)
For i = 0 To UBound(data)
WScript.StdOut.Write "value = " & data(i) &_
" running sd = " & sd(data,i)
WScript.StdOut.WriteLine
Next
Function sd(arr,n)
mean = 0
variance = 0
For j = 0 To n
mean = mean + arr(j)
Next
mean = mean/(n+1)
For k = 0 To n
variance = variance + ((arr(... |
Port the provided Pascal code into Go while preserving the original functionality. | program stddev;
uses math;
const
n=8;
var
arr: array[1..n] of real =(2,4,4,4,5,5,7,9);
function stddev(n: integer): real;
var
i: integer;
s1,s2,variance,x: real;
begin
for i:=1 to n do
begin
x:=arr[i];
s1:=s1+power(x,2);
s2:=s2+x
end;
variance:=((n*s1)-(power(s2,2)))/(power(n... | package main
import (
"fmt"
"math"
)
func newRsdv() func(float64) float64 {
var n, a, q float64
return func(x float64) float64 {
n++
a1 := a+(x-a)/n
q, a = q+(x-a)*(x-a1), a1
return math.Sqrt(q/n)
}
}
func main() {
r := newRsdv()
for _, x := range []float6... |
Generate an equivalent C version of this Perl code. | {
package SDAccum;
sub new {
my $class = shift;
my $self = {};
$self->{sum} = 0.0;
$self->{sum2} = 0.0;
$self->{num} = 0;
bless $self, $class;
return $self;
}
sub count {
my $self = shift;
return $self->{num};
}
sub mean {
my $self = shift;
return ($self->{num}>0) ? $self->{sum}/$sel... | #include <stdio.h>
#include <stdlib.h>
#include <math.h>
typedef enum Action { STDDEV, MEAN, VAR, COUNT } Action;
typedef struct stat_obj_struct {
double sum, sum2;
size_t num;
Action action;
} sStatObject, *StatObject;
StatObject NewStatObject( Action action )
{
StatObject so;
so = malloc(sizeof(sSta... |
Write the same code in C# as shown below in Perl. | {
package SDAccum;
sub new {
my $class = shift;
my $self = {};
$self->{sum} = 0.0;
$self->{sum2} = 0.0;
$self->{num} = 0;
bless $self, $class;
return $self;
}
sub count {
my $self = shift;
return $self->{num};
}
sub mean {
my $self = shift;
return ($self->{num}>0) ? $self->{sum}/$sel... | using System;
using System.Collections.Generic;
using System.Linq;
namespace standardDeviation
{
class Program
{
static void Main(string[] args)
{
List<double> nums = new List<double> { 2, 4, 4, 4, 5, 5, 7, 9 };
for (int i = 1; i <= nums.Count; i++)
... |
Write the same algorithm in C++ as shown in this Perl implementation. | {
package SDAccum;
sub new {
my $class = shift;
my $self = {};
$self->{sum} = 0.0;
$self->{sum2} = 0.0;
$self->{num} = 0;
bless $self, $class;
return $self;
}
sub count {
my $self = shift;
return $self->{num};
}
sub mean {
my $self = shift;
return ($self->{num}>0) ? $self->{sum}/$sel... | #include <assert.h>
#include <cmath>
#include <vector>
#include <iostream>
template<int N> struct MomentsAccumulator_
{
std::vector<double> m_;
MomentsAccumulator_() : m_(N + 1, 0.0) {}
void operator()(double v)
{
double inc = 1.0;
for (auto& mi : m_)
{
mi += inc;
inc *= v;
}
}
};
double Stdev(cons... |
Rewrite the snippet below in Java so it works the same as the original Perl code. | {
package SDAccum;
sub new {
my $class = shift;
my $self = {};
$self->{sum} = 0.0;
$self->{sum2} = 0.0;
$self->{num} = 0;
bless $self, $class;
return $self;
}
sub count {
my $self = shift;
return $self->{num};
}
sub mean {
my $self = shift;
return ($self->{num}>0) ? $self->{sum}/$sel... | public class StdDev {
int n = 0;
double sum = 0;
double sum2 = 0;
public double sd(double x) {
n++;
sum += x;
sum2 += x*x;
return Math.sqrt(sum2/n - sum*sum/n/n);
}
public static void main(String[] args) {
double[] testData = {2,4,4,4,5,5,7,9};
StdDev sd = new StdDev();
... |
Generate a Python translation of this Perl snippet without changing its computational steps. | {
package SDAccum;
sub new {
my $class = shift;
my $self = {};
$self->{sum} = 0.0;
$self->{sum2} = 0.0;
$self->{num} = 0;
bless $self, $class;
return $self;
}
sub count {
my $self = shift;
return $self->{num};
}
sub mean {
my $self = shift;
return ($self->{num}>0) ? $self->{sum}/$sel... | >>> from math import sqrt
>>> def sd(x):
sd.sum += x
sd.sum2 += x*x
sd.n += 1.0
sum, sum2, n = sd.sum, sd.sum2, sd.n
return sqrt(sum2/n - sum*sum/n/n)
>>> sd.sum = sd.sum2 = sd.n = 0
>>> for value in (2,4,4,4,5,5,7,9):
print (value, sd(value))
(2, 0.0)
(4, 1.0)
(4, 0.94280904158206258... |
Translate this program into VB but keep the logic exactly as in Perl. | {
package SDAccum;
sub new {
my $class = shift;
my $self = {};
$self->{sum} = 0.0;
$self->{sum2} = 0.0;
$self->{num} = 0;
bless $self, $class;
return $self;
}
sub count {
my $self = shift;
return $self->{num};
}
sub mean {
my $self = shift;
return ($self->{num}>0) ? $self->{sum}/$sel... | data = Array(2,4,4,4,5,5,7,9)
For i = 0 To UBound(data)
WScript.StdOut.Write "value = " & data(i) &_
" running sd = " & sd(data,i)
WScript.StdOut.WriteLine
Next
Function sd(arr,n)
mean = 0
variance = 0
For j = 0 To n
mean = mean + arr(j)
Next
mean = mean/(n+1)
For k = 0 To n
variance = variance + ((arr(... |
Generate a Go translation of this Perl snippet without changing its computational steps. | {
package SDAccum;
sub new {
my $class = shift;
my $self = {};
$self->{sum} = 0.0;
$self->{sum2} = 0.0;
$self->{num} = 0;
bless $self, $class;
return $self;
}
sub count {
my $self = shift;
return $self->{num};
}
sub mean {
my $self = shift;
return ($self->{num}>0) ? $self->{sum}/$sel... | package main
import (
"fmt"
"math"
)
func newRsdv() func(float64) float64 {
var n, a, q float64
return func(x float64) float64 {
n++
a1 := a+(x-a)/n
q, a = q+(x-a)*(x-a1), a1
return math.Sqrt(q/n)
}
}
func main() {
r := newRsdv()
for _, x := range []float6... |
Generate a C translation of this PowerShell snippet without changing its computational steps. | function Get-StandardDeviation {
begin {
$avg = 0
$nums = @()
}
process {
$nums += $_
$avg = ($nums | Measure-Object -Average).Average
$sum = 0;
$nums | ForEach-Object { $sum += ($avg - $_) * ($avg - $_) }
[Math]::Sqrt($sum / $nums.Length)
}
}
| #include <stdio.h>
#include <stdlib.h>
#include <math.h>
typedef enum Action { STDDEV, MEAN, VAR, COUNT } Action;
typedef struct stat_obj_struct {
double sum, sum2;
size_t num;
Action action;
} sStatObject, *StatObject;
StatObject NewStatObject( Action action )
{
StatObject so;
so = malloc(sizeof(sSta... |
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